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Fernando A. C. Gomide
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- affiliation: University of Campinas, Department of Computer Engineering and Automation, Campinas, São Paulo, Brazil
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2020 – today
- 2024
- [c98]Leandro Maciel, Rosangela Ballini, Fernando A. C. Gomide:
Adaptive Fuzzy Modeling and Forecasting of Financial Time Series. CIFEr 2024: 1-7 - [c97]Leandro Maciel, Fernando A. C. Gomide:
Recursive Level Set Fuzzy Modeling. EAIS 2024: 1-6 - 2023
- [j65]Daniel F. Leite
, Igor Skrjanc
, Saso Blazic
, Andrej Zdesar
, Fernando A. C. Gomide:
Interval incremental learning of interval data streams and application to vehicle tracking. Inf. Sci. 630: 1-22 (2023) - [j64]Leandro Maciel
, Rosangela Ballini
, Fernando A. C. Gomide
:
Adaptive fuzzy modeling of interval-valued stream data and application in cryptocurrencies prediction. Neural Comput. Appl. 35(10): 7149-7159 (2023) - [c96]Daniel F. Leite
, Fernando A. C. Gomide:
Data Driven Fuzzy and Neural Dynamic Systems Modeling. ICMLC 2023: 321-325 - [c95]Fernando A. C. Gomide, Ronald R. Yager:
Data Driven Level Set Fuzzy Classification. NAFIPS 2023: 36-43 - 2022
- [j63]Leandro Maciel
, Rosangela Ballini
, Fernando A. C. Gomide
, Ronald R. Yager
:
Forecasting cryptocurrencies prices using data driven level set fuzzy models. Expert Syst. Appl. 210: 118387 (2022) - [j62]Alisson Porto, Fernando A. C. Gomide:
Evolving hyperbox fuzzy modeling. Evol. Syst. 13(3): 423-434 (2022) - [j61]Ildar Z. Batyrshin, Fernando A. C. Gomide, Vladik Kreinovich, Shahnaz N. Shahbazova:
Soft computing and advances in intelligent systems. J. Intell. Fuzzy Syst. 43(6): 6895-6896 (2022) - [c94]Daniel F. Leite
, Fernando A. C. Gomide, Ronald R. Yager:
Data Driven Fuzzy Modeling Using Level Sets. FUZZ-IEEE 2022: 1-5 - [c93]Lucas Morais, Rodrigo Gonçalves, Alexandre Tazoniero, Fernando A. C. Gomide:
Algorithms for Freight Train Scheduling. IJCCI 2022: 74-81 - [c92]Leandro Maciel, Rosangela Ballini, Fernando A. C. Gomide:
Data Driven Level Set Fuzzy Modeling for Cryptocurrencies Price Forecasting. IJCCI 2022: 193-198 - [c91]Leandro Maciel, Rosangela Ballini, Fernando A. C. Gomide:
Data Driven Level Set Method in Fuzzy Modeling and Forecasting. NAFIPS 2022: 125-134 - 2021
- [j60]Anderson Bento, Lucas Oliveira
, Ignácio Rubio Scola
, Valter J. S. Leite
, Fernando A. C. Gomide
:
Evolving granular control with high-gain observers for feedback linearizable nonlinear systems. Evol. Syst. 12(4): 935-948 (2021) - [c90]Gabriela de Castro Surita, André P. Lemos, Fernando A. C. Gomide:
Fuzzy Baselines to Stabilize Policy Gradient Reinforcement Learning. NAFIPS 2021: 436-446 - [p7]Fernando A. C. Gomide, André P. Lemos, Walmir M. Caminhas
:
Evolving Systems. Fuzzy Approaches for Soft Computing and Approximate Reasoning 2021: 169-178 - 2020
- [j59]Lucas Oliveira
, Anderson Bento, Valter J. S. Leite
, Fernando A. C. Gomide:
Evolving granular feedback linearization: Design, analysis, and applications. Appl. Soft Comput. 86 (2020) - [j58]Daniel F. Leite
, Igor Skrjanc, Fernando A. C. Gomide:
An overview on evolving systems and learning from stream data. Evol. Syst. 11(2): 181-198 (2020) - [j57]Daniel F. Leite
, Goran Andonovski, Igor Skrjanc
, Fernando A. C. Gomide
:
Optimal Rule-Based Granular Systems From Data Streams. IEEE Trans. Fuzzy Syst. 28(3): 583-596 (2020) - [c89]Leandro Maciel
, Rosangela Ballini
, Fernando A. C. Gomide:
A Fuzzy Model for Interval-Valued Time Series Modeling and Application in Exchange Rate Forecasting. IPMU (3) 2020: 41-53 - [c88]Leandro Maciel, Rosangela Ballini, Fernando A. C. Gomide:
Adaptive Interval Fuzzy Modeling from Stream Data and Application in Cryptocurrencies Forecasting. NAFIPS 2020: 69-81
2010 – 2019
- 2019
- [j56]Igor Skrjanc
, José Antonio Iglesias
, Araceli Sanchis, Daniel F. Leite
, Edwin Lughofer, Fernando A. C. Gomide:
Evolving fuzzy and neuro-fuzzy approaches in clustering, regression, identification, and classification: A Survey. Inf. Sci. 490: 344-368 (2019) - [c87]Allison Porto, Fernando A. C. Gomide:
Granular Evolving Min-Max Fuzzy Modeling. EUSFLAT Conf. 2019 - [c86]Daniel F. Leite
, Fernando A. C. Gomide, Igor Skrjanc:
Multiobjective Optimization of Fully Autonomous Evolving Fuzzy Granular Models. FUZZ-IEEE 2019: 1-7 - [c85]Lucas Oliveira, Valter J. S. Leite
, Anderson Bento, Fernando A. C. Gomide:
Robust Granular Feedback Linearization. FUZZ-IEEE 2019: 1-6 - [c84]Lucas Oliveira, Anderson Bento, Valter J. S. Leite
, Fernando A. C. Gomide:
Robust Evolving Granular Feedback Linearization. IFSA/NAFIPS 2019: 442-452 - 2018
- [c83]Rafael Vieira, Fernando A. C. Gomide, Rosangela Ballini
:
Kernel Evolving Participatory Fuzzy Modeling for Time Series Forecasting. FUZZ-IEEE 2018: 1-9 - [c82]Alisson Porto, Fernando A. C. Gomide:
Evolving Granular Fuzzy Min-Max Modeling. NAFIPS 2018: 37-48 - [c81]Rafael Vieira, Leandro Maciel
, Rosangela Ballini
, Fernando A. C. Gomide:
Stock Market Price Forecasting Using a Kernel Participatory Learning Fuzzy Model. NAFIPS 2018: 361-373 - 2017
- [j55]Leandro Maciel
, Rosangela Ballini
, Fernando A. C. Gomide:
An evolving possibilistic fuzzy modeling approach for Value-at-Risk estimation. Appl. Soft Comput. 60: 820-830 (2017) - [j54]Yi-Ling Liu, Fernando A. C. Gomide:
A participatory search algorithm. Evol. Intell. 10(1-2): 23-43 (2017) - [j53]Leandro Maciel
, Rosangela Ballini
, Fernando A. C. Gomide:
Evolving Possibilistic Fuzzy Modeling for Realized Volatility Forecasting With Jumps. IEEE Trans. Fuzzy Syst. 25(2): 302-314 (2017) - [c80]Yi-Ling Liu, Fernando A. C. Gomide:
Participatory Search in Evolutionary Fuzzy Modeling. Soft Computing Based Optimization and Decision Models 2017: 191-212 - [c79]Leandro Maciel
, Rafael Vieira, Alisson Porto, Fernando A. C. Gomide, Rosangela Ballini
:
Evolving participatory learning fuzzy modeling for financial interval time series forecasting. EAIS 2017: 1-8 - [c78]Lucas Oliveira, Valter J. S. Leite
, Jeferson Silva, Fernando A. C. Gomide:
Granular evolving fuzzy robust feedback linearization. EAIS 2017: 1-8 - [c77]Yi-Ling Liu, Fernando A. C. Gomide:
Fuzzy systems modeling with participatory search algorithm. IFSA-SCIS 2017: 1-6 - [c76]Alisson Porto, Fernando A. C. Gomide:
Evolving Granular Fuzzy Min-Max Regression. NAFIPS 2017: 162-171 - [p6]Leandro Maciel
, Rosangela Ballini
, Fernando A. C. Gomide:
Evolving Possibilistic Fuzzy Modeling and Application in Value-at-Risk Estimation. Granular, Soft and Fuzzy Approaches for Intelligent Systems 2017: 119-139 - 2016
- [j52]Leandro Maciel
, Fernando A. C. Gomide, Rosangela Ballini
:
A differential evolution algorithm for yield curve estimation. Math. Comput. Simul. 129: 10-30 (2016) - [c75]Leandro Maciel
, Rosangela Ballini
, Fernando A. C. Gomide:
Evolving possibilistic fuzzy modeling for equity options pricing. EAIS 2016: 57-64 - [c74]Daniel F. Leite
, Marcio Santana, Ana Borges, Fernando A. C. Gomide:
Fuzzy Granular Neural Network for incremental modeling of nonlinear chaotic systems. FUZZ-IEEE 2016: 64-71 - [c73]Leandro Maciel
, Rosangela Ballini
, Fernando A. C. Gomide, Ronald R. Yager:
Participatory Learning Fuzzy Clustering for Interval-Valued Data. IPMU (1) 2016: 687-698 - [c72]Ranyeri Rocha, Fernando A. C. Gomide:
Performance evaluation of evolving classifier algorithms in high dimensional spaces. NAFIPS 2016: 1-6 - [e1]Víctor Flores, Fernando A. C. Gomide, Andrzej Janusz
, Claudio Meneses, Duoqian Miao, Georg Peters, Dominik Slezak
, Guoyin Wang, Richard Weber, Yiyu Yao:
Rough Sets - International Joint Conference, IJCRS 2016, Santiago de Chile, Chile, October 7-11, 2016, Proceedings. Lecture Notes in Computer Science 9920, 2016, ISBN 978-3-319-47159-4 [contents] - 2015
- [j51]Alisson Marques Silva
, Walmir M. Caminhas
, André P. Lemos, Fernando A. C. Gomide:
Adaptive Input Selection and Evolving Neural Fuzzy Networks Modeling. Int. J. Comput. Intell. Syst. 8(sup1): 3-14 (2015) - [j50]Daniel F. Leite
, Reinaldo M. Palhares
, Víctor C. S. Campos
, Fernando A. C. Gomide:
Evolving Granular Fuzzy Model-Based Control of Nonlinear Dynamic Systems. IEEE Trans. Fuzzy Syst. 23(4): 923-938 (2015) - [c71]Leandro Maciel, André Paim Lemos, Rosangela Ballini, Fernando A. C. Gomide:
Adaptive Fuzzy C-Regression Modeling for Time Series Forecasting. IFSA-EUSFLAT 2015 - [c70]Leandro Maciel
, Fernando A. C. Gomide, Rosangela Ballini
:
Evolving possibilistic fuzzy modeling. FUZZ-IEEE 2015: 1-8 - [c69]Leandro Maciel
, Fernando A. C. Gomide, Rosangela Ballini
:
Evolving possibilistic fuzzy modeling for financial interval time series forecasting. NAFIPS/WConSC 2015: 1-6 - [p5]Daniel F. Leite
, Fernando A. C. Gomide:
Incremental Granular Fuzzy Modeling Using Imprecise Data Streams. Fifty Years of Fuzzy Logic and its Applications 2015: 107-124 - 2014
- [j49]Alisson Marques Silva
, Walmir M. Caminhas
, André Paim Lemos, Fernando A. C. Gomide:
A fast learning algorithm for evolving neo-fuzzy neuron. Appl. Soft Comput. 14: 194-209 (2014) - [j48]Leandro Maciel
, Fernando A. C. Gomide, Rosangela Ballini
:
Enhanced evolving participatory learning fuzzy modeling: an application for asset returns volatility forecasting. Evol. Syst. 5(2): 75-88 (2014) - [j47]Fernando A. C. Gomide, Edwin Lughofer:
Recent advances on evolving intelligent systems and applications. Evol. Syst. 5(4): 217-218 (2014) - [j46]Fernando Bordignon, Fernando A. C. Gomide:
Uninorm based evolving neural networks and approximation capabilities. Neurocomputing 127: 13-20 (2014) - [c68]Alisson Marques Silva
, Walmir M. Caminhas
, André Paim Lemos, Fernando A. C. Gomide:
Real-time nonlinear modeling of a twin rotor MIMO system using evolving neuro-fuzzy network. CICA 2014: 29-36 - [c67]Michel Hell
, Pyramo Costa, Fernando A. C. Gomide:
Participatory learning in the neurofuzzy short-term load forecasting. CIES 2014: 176-182 - [c66]Leandro Maciel
, Fernando A. C. Gomide, David Santos, Rosangela Ballini
:
Exchange rate forecasting using echo state networks for trading strategies. CIFEr 2014: 40-47 - [c65]Raul Rosa, Leandro Maciel
, Fernando A. C. Gomide, Rosangela Ballini
:
Evolving hybrid neural fuzzy network for realized volatility forecasting with jumps. CIFEr 2014: 481-488 - [c64]Raul Rosa, Fernando A. C. Gomide, Dejan Dovzan, Igor Skrjanc:
Evolving neural network with extreme learning for system modeling. EAIS 2014: 1-7 - [c63]Igor Skrjanc, Dejan Dovzan, Fernando A. C. Gomide:
Evolving fuzzy-madel-based on c-regression clustering. EAIS 2014: 1-7 - [c62]Leandro Maciel
, Fernando A. C. Gomide, Rosangela Ballini
:
Recursive possibilistic fuzzy modeling. EALS 2014: 9-16 - 2013
- [j45]André Paim Lemos, Walmir M. Caminhas
, Fernando A. C. Gomide:
Adaptive fault detection and diagnosis using an evolving fuzzy classifier. Inf. Sci. 220: 64-85 (2013) - [j44]Daniel F. Leite
, Pyramo Costa Jr., Fernando A. C. Gomide:
Evolving granular neural networks from fuzzy data streams. Neural Networks 38: 1-16 (2013) - [c61]Fernando A. C. Gomide:
On Fuzziness. On Fuzziness (1) 2013: 217-222 - [c60]Leandro Maciel
, Fernando A. C. Gomide, Rosangela Ballini
, Ronald R. Yager:
Simplified evolving rule-based fuzzy modeling of realized volatility forecasting with jumps. CIFEr 2013: 82-89 - [c59]Leandro Maciel, Fernando A. C. Gomide, Rosangela Ballini:
Forecasting Exchange Rates with Fuzzy Granular Evolving Modeling for Trading Strategies. EUSFLAT Conf. 2013 - [c58]Yi-Ling Liu, Fernando A. C. Gomide:
Evolutionary participatory learning in fuzzy systems modeling. FUZZ-IEEE 2013: 1-8 - [c57]Yi-Ling Liu, Fernando A. C. Gomide:
Genetic participatory algorithm and system modeling. GECCO (Companion) 2013: 1687-1690 - [c56]Yi-Ling Liu, Fernando A. C. Gomide:
Participatory genetic learning in fuzzy system modeling. GEFS 2013: 1-7 - [c55]Raul Rosa, Fernando A. C. Gomide, Rosangela Ballini
:
Evolving Hybrid Neural Fuzzy Network for System Modeling and Time Series Forecasting. ICMLA (2) 2013: 378-383 - [c54]Yi-Ling Liu, Fernando A. C. Gomide:
Fuzzy systems modeling with participatory evolution. IFSA/NAFIPS 2013: 380-385 - [p4]André Paim Lemos, Rosangela Ballini, Walmir M. Caminhas
, Fernando A. C. Gomide:
System Modeling and Forecasting with Evolving Fuzzy Algorithms. Soft Computing: State of the Art Theory and Novel Applications 2013: 255-268 - 2012
- [j43]Leandro Maciel
, André Paim Lemos, Fernando A. C. Gomide, Rosangela Ballini
:
Evolving fuzzy systems for pricing fixed income options. Evol. Syst. 3(1): 5-18 (2012) - [j42]Daniel F. Leite
, Rosangela Ballini
, Pyramo Costa Jr., Fernando A. C. Gomide:
Evolving fuzzy granular modeling from nonstationary fuzzy data streams. Evol. Syst. 3(2): 65-79 (2012) - [c53]Leandro Maciel
, Fernando A. C. Gomide, Rosangela Ballini
:
MIMO evolving functional fuzzy models for interest rate forecasting. CIFEr 2012: 1-8 - [c52]Leandro Maciel
, Fernando A. C. Gomide, Rosangela Ballini
:
Modeling the term structure of government bond yields with a differential evolution algorithm. CIFEr 2012: 1-8 - [c51]Leandro Maciel
, Fernando A. C. Gomide, Rosangela Ballini
:
An enhanced approach for evolving participatory learning fuzzy modeling. EAIS 2012: 23-28 - [c50]André Paim Lemos, Daniel F. Leite
, Leandro Maciel
, Rosangela Ballini
, Walmir M. Caminhas
, Fernando A. C. Gomide:
Evolving fuzzy linear regression tree approach for forecasting sales volume of petroleum products. FUZZ-IEEE 2012: 1-8 - [c49]Leandro Maciel
, Fernando A. C. Gomide, Rosangela Ballini
:
MIMO evolving participatory learning fuzzy modeling. FUZZ-IEEE 2012: 1-8 - [c48]Alisson Marques Silva
, Walmir Matos Caminhas
, André Paim Lemos, Fernando A. C. Gomide:
Evolving Neural Fuzzy Network with Adaptive Feature Selection. ICMLA (2) 2012: 440-445 - [c47]Daniel F. Leite
, Pyramo Costa Jr., Fernando A. C. Gomide:
Evolving granular neural network for fuzzy time series forecasting. IJCNN 2012: 1-8 - [c46]Leandro Maciel
, Fernando A. C. Gomide, Rosangela Ballini
:
Evolving Fuzzy Modeling for Stock Market Forecasting. IPMU (4) 2012: 20-29 - [c45]Fernando Bordignon, Fernando A. C. Gomide:
Extreme Learning for Evolving Hybrid Neural Networks. SBRN 2012: 196-201 - [p3]Daniel F. Leite, Fernando A. C. Gomide:
Evolving Linguistic Fuzzy Models from Data Streams. Combining Experimentation and Theory 2012: 209-223 - 2011
- [j41]Vitor Marques, Fernando A. C. Gomide:
Parameter control of metaheuristics with genetic fuzzy systems. Evol. Intell. 4(3): 183-202 (2011) - [j40]André Paim Lemos, Walmir M. Caminhas
, Fernando A. C. Gomide:
Fuzzy evolving linear regression trees. Evol. Syst. 2(1): 1-14 (2011) - [j39]André Paim Lemos, Walmir M. Caminhas
, Fernando A. C. Gomide:
Multivariable Gaussian Evolving Fuzzy Modeling System. IEEE Trans. Fuzzy Syst. 19(1): 91-104 (2011) - [c44]Gustavo de Oliveira Aggio
, Rosangela Ballini
, Fernando A. C. Gomide:
Out-of-equilibrium price dynamics and the inflationary process. CIFEr 2011: 1-8 - [c43]André Paim Lemos, Walmir M. Caminhas
, Fernando A. C. Gomide:
Evolving fuzzy linear regression trees with feature selection. EAIS 2011: 31-38 - [c42]Leandro Maciel
, Fernando A. C. Gomide, Rosangela Ballini
:
Evolving fuzzy systems for pricing fixed income options. EAIS 2011: 54-61 - [c41]Daniel F. Leite
, Fernando A. C. Gomide, Rosangela Ballini
, Pyramo Costa Jr.:
Fuzzy granular evolving modeling for time series prediction. FUZZ-IEEE 2011: 2794-2801 - 2010
- [c40]Rosangela Ballini
, Fernando A. C. Gomide:
Recurrent fuzzy neural computation: Modeling, learning and application. FUZZ-IEEE 2010: 1-6 - [c39]André Paim Lemos, Walmir Matos Caminhas
, Fernando A. C. Gomide:
Evolving fuzzy linear regression trees. FUZZ-IEEE 2010: 1-8 - [c38]Vitor Marques, Fernando A. C. Gomide:
Memory control of tabu search with genetic fuzzy systems. FUZZ-IEEE 2010: 1-7 - [c37]Vitor Marques, Fernando A. C. Gomide:
Fuzzy coordination of genetic algorithms for vehicle routing problems with time windows. GEFS 2010: 39-44 - [c36]Daniel F. Leite
, Pyramo Costa Jr., Fernando A. C. Gomide:
Evolving granular neural network for semi-supervised data stream classification. IJCNN 2010: 1-8 - [c35]Daniel F. Leite
, Pyramo Costa Jr., Fernando A. C. Gomide:
Granular Approach for Evolving System Modeling. IPMU 2010: 340-349 - [c34]André Paim Lemos, Walmir M. Caminhas
, Fernando A. C. Gomide:
Fuzzy Multivariable Gaussian Evolving Approach for Fault Detection and Diagnosis. IPMU 2010: 360-369
2000 – 2009
- 2009
- [j38]Igor Walter, Fernando A. C. Gomide:
Multiagent coevolutionary genetic fuzzy system to develop bidding strategies in electricity markets: computational economics to assess mechanism design. Evol. Intell. 2(1-2): 53-71 (2009) - [j37]Rachel Pereira, Ivan Ricarte, Fernando A. C. Gomide:
Information retrieval with FROM: The fuzzy relational ontological model. Int. J. Intell. Syst. 24(3): 340-356 (2009) - [j36]Rosangela Ballini, A. R. R. Mendonça, Fernando A. C. Gomide:
Evolving fuzzy modelling in risk analysis. Intell. Syst. Account. Finance Manag. 16(1-2): 71-86 (2009) - [j35]Rosana Motta Jafelice
, B. F. Z. Bechara, Laécio C. Barros, Rodney Carlos Bassanezi, Fernando A. C. Gomide:
Cellular automata with fuzzy parameters in microscopic study of positive HIV individuals. Math. Comput. Model. 50(1-2): 32-44 (2009) - [c33]Igor Walter, Fernando A. C. Gomide:
Coevolutionary Genetic Fuzzy System to Assess Multiagent Bidding Strategies in Electricity Markets. IFSA/EUSFLAT Conf. 2009: 1114-1119 - [c32]Daniel F. Leite
, Pyramo Costa Jr., Fernando A. C. Gomide:
Evolving granular classification neural networks. IJCNN 2009: 1736-1743 - 2008
- [j34]Yurilev Chalco-Cano
, Heriberto Román-Flores, Fernando A. C. Gomide:
A new type of approximation for fuzzy intervals. Fuzzy Sets Syst. 159(11): 1376-1383 (2008) - [c31]Igor Walter, Fernando A. C. Gomide:
Coevolutionary fuzzy multiagent bidding strategies in competitive electricity markets. GEFS 2008: 53-58 - [c30]Michel Hell
, Pyramo Costa Jr., Fernando A. C. Gomide:
Hybrid neurofuzzy computing with nullneurons. IJCNN 2008: 3653-3659 - [c29]Igor Walter, Fernando A. C. Gomide:
Electricity market simulation: multiagent system approach. SAC 2008: 34-38 - [c28]Michel Hell
, Fernando A. C. Gomide, Pyramo Costa Jr.:
Neurons and Neural Fuzzy Networks Based on Nullnorms. SBRN 2008: 123-128 - 2007
- [b1]Witold Pedrycz, Fernando A. C. Gomide:
Fuzzy Systems Engineering - Toward Human-Centric Computing. Wiley 2007, ISBN 978-0-471-78857-7, pp. I-XXII, 1-526 - [j33]Fernando A. C. Gomide:
Zdzislaw Bubnicki, Analysis and Decision Making in Uncertain Systems, Springer, London (2004) ISBN 1852337729. Fuzzy Sets Syst. 158(24): 2767-2768 (2007) - [j32]Igor Walter, Fernando A. C. Gomide:
Genetic fuzzy systems to evolve interaction strategies in multiagent systems. Int. J. Intell. Syst. 22(9): 971-991 (2007) - [j31]Giselle Cardoso, Fernando A. C. Gomide:
Newspaper demand prediction and replacement model based on fuzzy clustering and rules. Inf. Sci. 177(21): 4799-4809 (2007) - [c27]Michel Hell, Rosangela Ballini, Pyramo Costa Jr., Fernando A. C. Gomide:
Training Neurofuzzy Networks with Participatory Learning. EUSFLAT Conf. (2) 2007: 231-236 - [c26]Michel Hell
, Pyramo Costa Jr., Fernando A. C. Gomide:
New Neurofuzzy Training Procedure Based on Participatory Learning Paradigm. FUZZ-IEEE 2007: 1-6 - [c25]Wanessa Amaral, Fernando A. C. Gomide:
An Algorithm to Solve Two-Person Non-zero Sum Fuzzy Games. IFSA (2) 2007: 296-302 - [p2]Alexandre Tazoniero, Rodrigo Gonçalves, Fernando A. C. Gomide:
Decision Making Strategies for Real-Time Train Dispatch and Control. Analysis and Design of Intelligent Systems using Soft Computing Techniques 2007: 195-204 - 2006
- [j30]Marley M. B. R. Vellasco, Fernando A. C. Gomide:
Special issue: Hybrid intelligent systems in ensembles. Int. J. Hybrid Intell. Syst. 3(3): 127-128 (2006) - [j29]Igor Walter, Fernando A. C. Gomide:
Design of coordination strategies in multiagent systems via genetic fuzzy systems. Soft Comput. 10(10): 903-915 (2006) - [c24]Francisco Mota Filho, Fernando A. C. Gomide:
Fuzzy Clustering in Fitness Estimation Models for Genetic Algorithms and Applications. FUZZ-IEEE 2006: 1388-1395 - [p1]Rachel Pereira, Ivan Ricarte, Fernando A. C. Gomide:
Fuzzy relational ontological model in information search systems. Fuzzy Logic and the Semantic Web 2006: 395-412 - 2005
- [j28]Rosana Motta Jafelice
, Laécio Carvalho de Barros, Rodney Carlos Bassanezi, Fernando A. C. Gomide:
Methodology To Determine The Evolution Of Asymptomatic Hiv Population Using Fuzzy Set Theory. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 13(1): 39-58 (2005) - [c23]Francisco Mota Filho, Fernando A. C. Gomide:
Hybrid Genetic Algorithms and Clustering. EUSFLAT Conf. 2005: 1009-1016 - [c22]Leila Roling Scariot da Silva, Fernando A. C. Gomide, Ronald R. Yager:
Participatory Learning in Fuzzy Clustering. FUZZ-IEEE 2005: 857-861 - [c21]Michel Hell
, Luiz Secco, Pyramo Costa Jr., Fernando A. C. Gomide:
Recurrent Neural Approaches for Power Transformers Thermal Modeling. PReMI 2005: 287-293 - 2004
- [j27]Oscar Cordón
, Fernando A. C. Gomide, Francisco Herrera
, Frank Hoffmann, Luis Magdalena
:
Genetic fuzzy systems. New developments. Fuzzy Sets Syst. 141(1): 1-3 (2004) - [j26]Oscar Cordón
, Fernando A. C. Gomide, Francisco Herrera
, Frank Hoffmann, Luis Magdalena
:
Ten years of genetic fuzzy systems: current framework and new trends. Fuzzy Sets Syst. 141(1): 5-31 (2004) - [j25]Myriam Regattieri Delgado, Fernando J. Von Zuben
, Fernando A. C. Gomide:
Coevolutionary genetic fuzzy systems: a hierarchical collaborative approach. Fuzzy Sets Syst. 141(1): 89-106 (2004) - [j24]Maurício F. Figueiredo, Rosangela Ballini
, Secundino Soares
, Marinho Gomes Andrade, Fernando A. C. Gomide:
Learning algorithms for a class of neurofuzzy network and application. IEEE Trans. Syst. Man Cybern. Part C 34(3): 293-301 (2004) - [c20]Marina H. Magalhaes, Rosangela Ballini
, Rodrigo Gonçalves, Fernando A. C. Gomide:
Predictive fuzzy clustering model for natural streamflow forecasting. FUZZ-IEEE 2004: 1349-1354 - 2003
- [j23]Fernando A. C. Gomide:
Book Review: "Uncertain rule-based fuzzy logic systems: introduction and new directions" by Jerry M. Mendel. Fuzzy Sets Syst. 133(1): 133-135 (2003) - [j22]Fernando A. C. Gomide:
Book Review: "Practical applications of fuzzy technologies" by Hans-Jürgen Zimmermann (Ed.), in "The Handbook of Fuzzy Sets Series", Didier Dubois and Henri Prade (Series Eds.), Kluwer Academic Publishers, Boston/London/Dordrecht, 1999, 677pp, ISBN 0-7923-8628-0. Fuzzy Sets Syst. 139(1): 239-242 (2003) - [j21]Fernando A. C. Gomide:
Book Review: "Fuzzy engineering expert systems with neural network applications" by Adedeji B. Badiru and John Y. Cheung; Wiley, New York, 2002, 291 pp., ISBN 0-471-29331-8. Fuzzy Sets Syst. 140(2): 397-398 (2003) - [j20]Roseli A. Francelin Romero, Fernando A. C. Gomide:
Qualitative analysis and synthesis of recurrent neural networks [Book Review]. IEEE Trans. Neural Networks 14(6): 1580-1581 (2003) - [c19]Brian Carse, Anthony G. Pipe, Ingo Renners, Adolf Grauel, Antonio Fernandez Gómez-Skarmeta, Fernando Jiménez, Gracia Sánchez, Oscar Cordón, Francisco Herrera, Fernando A. C. Gomide, Igor Walter, Antonio González Muñoz, Raúl Pérez:
Current issues and future directions in evolutionary fuzzy systems research. EUSFLAT Conf. 2003: 81-87 - [c18]Igor Walter, Fernando A. C. Gomide:
Genetic fuzzy systems to evolve coordination strategies in competitive distributed systems. EUSFLAT Conf. 2003: 114-119 - [c17]Rosangela Ballini, Fernando A. C. Gomide:
Gradient Projection Method and Equality Index in Recurrent Neural Fuzzy Network. IFSA 2003: 585-594 - [c16]Igor Walter, Fernando A. C. Gomide:
Evolving fuzzy bidding strategies in competitive electricity markets. SMC 2003: 3976-3981 - 2002
- [j19]Rosangela Ballini, Fernando A. C. Gomide:
Heuristic learning in recurrent neural fuzzy networks. J. Intell. Fuzzy Syst. 13(2-4): 63-74 (2002) - [c15]Myriam Regattieri Delgado, Fernando J. Von Zuben
, Fernando A. C. Gomide:
Coevolutionary design of Takagi-Sugeno fuzzy systems. IEEE Congress on Evolutionary Computation 2002: 1384-1389 - [c14]Rosangela Ballini, Fernando A. C. Gomide:
Learning in recurrent, hybrid neurofuzzy networks. FUZZ-IEEE 2002: 785-790 - [c13]Myriam Regattieri Delgado, Fernando J. Von Zuben, Fernando A. C. Gomide:
Multi-objective decision making: towards improvement of accuracy, interpretability and design autonomy in hierarchical genetic fuzzy systems. FUZZ-IEEE 2002: 1222-1227 - [c12]Rosangela Ballini
, Fernando A. C. Gomide:
A Recurrent Fuzzy Neural Network: Learning and Application. SBRN 2002: 153 - 2001
- [j18]José Valente de Oliveira
, Fernando A. C. Gomide:
Formal Methods for Fuzzy Modeling and Control. Fuzzy Sets Syst. 121(1): 1-2 (2001) - [j17]Roseli A. Francelin Romero, Janusz Kacprzyk, Fernando A. C. Gomide:
A Biologically Inspired Neural Network For Dynamic Programming. Int. J. Neural Syst. 11(6): 561-572 (2001) - [j16]Myriam Regattieri Delgado, Fernando J. Von Zuben
, Fernando A. C. Gomide:
Hierarchical genetic fuzzy systems. Inf. Sci. 136(1-4): 29-52 (2001) - [c11]Rosangela Ballini, Fernando A. C. Gomide, Secundino Soares:
A Recurrent Neurofuzzy Network Structure & Learning Preceedure. FUZZ-IEEE 2001: 1408-1411 - 2000
- [c10]Carlos Pinheiro, Fernando A. C. Gomide:
On tuning nonlinear fuzzy control systems. FUZZ-IEEE 2000: 146-151 - [c9]Myriam Regattieri Delgado, Fernando J. Von Zuben, Fernando A. C. Gomide:
Evolutionary design of Takagi-Sugeno fuzzy systems: a modular and hierarchical approach. FUZZ-IEEE 2000: 447-452
1990 – 1999
- 1999
- [j15]Janusz Kacprzyk, Roseli A. Francelin Romero, Fernando A. C. Gomide:
Involving objective and subjective aspects in multistage decision making and control under fuzziness: Dynamic programming and neural networks. Int. J. Intell. Syst. 14(1): 79-104 (1999) - [j14]Heloisa A. Camargo, Fernando A. C. Gomide:
Hierarchical fuzzy Petri nets and α-level sets inference. Int. J. Intell. Syst. 14(8): 859-871 (1999) - [j13]Walmir M. Caminhas, Hermano Tavares, Fernando A. C. Gomide, Witold Pedrycz:
Fuzzy Set Based Neural Networks: Structure, Learning and Application. J. Adv. Comput. Intell. Intell. Informatics 3(3): 151-157 (1999) - [j12]Maurício F. Figueiredo, Fernando A. C. Gomide:
Design of fuzzy systems using neurofuzzy networks. IEEE Trans. Neural Networks 10(4): 815-827 (1999) - [c8]Eduardo Masato Iyoda, Leandro Nunes de Castro
, Fernando A. C. Gomide, Fernando J. Von Zuben
:
Evolutionary design of neurofuzzy networks for pattern classification. CEC 1999: 1237-1244 - [c7]Myriam Regattieri Delgado, Fernando J. Von Zuben, Fernando A. C. Gomide:
Modular and Hierarchial Evolutionary Design of Fuzzy Systems. GECCO 1999: 180-187 - [c6]Carlos Pinheiro, Fernando A. C. Gomide:
Neural control of nonlinear systems by frequency response. IJCNN 1999: 2119-2122 - [c5]Leandro Nunes de Castro, Luis Alberto Ramirez, Fernando A. C. Gomide, Fernando J. Von Zuben:
Hybrid tuning of activation functions in feedforward neural networks. IJCNN 1999: 4263-4268 - 1998
- [j11]Ricardo R. Gudwin, Fernando A. C. Gomide, Witold Pedrycz:
Context adaptation in fuzzy processing and genetic algorithms. Int. J. Intell. Syst. 13(10-11): 929-948 (1998) - 1997
- [j10]Witold Pedrycz, Ricardo R. Gudwin
, Fernando A. C. Gomide:
Nonlinear context adaptation in the calibration of fuzzy sets. Fuzzy Sets Syst. 88(1): 91-97 (1997) - [c4]Maurício F. Figueiredo, Fernando A. C. Gomide:
A neural fuzzy approach for fuzzy system design. ICNN 1997: 420-425 - 1996
- [j9]Maurício F. Figueiredo, Fernando A. C. Gomide:
Regular policies and stability of dynamic scheduling for manufacturing systems. Comput. Oper. Res. 23(10): 963-979 (1996) - [j8]Heloisa Scarpelli, Fernando A. C. Gomide, Witold Pedrycz:
Modeling fuzzy Reasoning using High Level fuzzy Petri Nets. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 4(1): 61-86 (1996) - [j7]Heloisa Scarpelli, Fernando A. C. Gomide, Ronald R. Yager:
A reasoning algorithm for high-level fuzzy Petri nets. IEEE Trans. Fuzzy Syst. 4(3): 282-294 (1996) - [j6]Ricardo R. Gudwin
, Fernando A. C. Gomide, Márcio L. Andrade Netto, Maurício F. Magalhães:
Knowledge Processing in Control Systems. IEEE Trans. Knowl. Data Eng. 8(1): 106-119 (1996) - 1994
- [j5]Witold Pedrycz, Fernando A. C. Gomide:
A generalized fuzzy Petri net model. IEEE Trans. Fuzzy Syst. 2(4): 295-301 (1994) - [c3]Ricardo R. Gudwin, Fernando A. C. Gomide:
Genetic Algorithms and Discrete Event Systems: An Application. International Conference on Evolutionary Computation 1994: 742-745 - 1993
- [j4]Heloisa Scarpelli, Fernando A. C. Gomide:
Fuzzy Reasoning and Fuzzy Petri Nets in Manufacturing Systems Modeling. J. Intell. Fuzzy Syst. 1(3): 225-241 (1993) - [j3]Maurício F. Figueiredo, Fernando A. C. Gomide, Armando Rocha, Ronald R. Yager:
Comparison of Yager's level set method for fuzzy logic control with Mamdani's and Larsen's methods. IEEE Trans. Fuzzy Syst. 1(2): 156-159 (1993) - [c2]Roseli Aparecida Francelin Romero, Fernando A. C. Gomide:
A neural network to solve discrete dynamic programming problems. ICNN 1993: 1433-1438 - 1991
- [j2]Fernando Antonio Campos Gomide, JoséRoberto Cardarelli, Kyösti Tarvainen:
Large scale systems with multiple objectives: An interactive negotiation procedure. Autom. 27(4): 691-697 (1991)
1980 – 1989
- 1989
- [c1]Edilberto Pereira Teixeira, Fernando A. C. Gomide:
Extreme conditions for one step convergence of the Hopfield neural network. SMC 1989: 220-221 - 1984
- [j1]Fernando A. C. Gomide, Yacov Y. Haimes:
The multiobjective multistage impact analysis method: Theoretical basis. IEEE Trans. Syst. Man Cybern. 14(1): 88-98 (1984)
Coauthor Index
aka: Walmir Matos Caminhas
aka: Pyramo Costa Jr.
aka: André Paim Lemos
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